Nurse Perspectives on Family-Centred Rounds in Adult Critical Care Units
Bibliographic record
Abstract
Background: In critical care settings, family involvement in care is important. Family-centred rounds (FCR) are often seen as a component of family-centred care. Nurses have an important role in implementing FCR and their active participation is crucial. There is currently a lack of rigorous literature that explores nursing perspectives of FCR in adult critical care areas. Purpose: This study explored nursing perspectives (n = 135) of FCR in six adult critical care units across four Southwestern Ontario hospitals. Methods: A 56-question survey was distributed to critical care nurses currently working in one of the adult critical care units under study through an online Qualtrics® link. This research explored nursing perspectives of FCR, so nurses did not need to have experience participating in FCR to take part in this study. Results: The descriptive results highlighted the structures and processes that nurses felt would best support them during FCR. Additionally, nurses noted the greatest advantage of FCR was that the healthcare team can update the family on the patient’s condition, and the greatest barrier to FCR is the inconsistent or unknown timing of rounds. Tests of association revealed that nurses’ overall supportiveness of FCR was statistically significantly related to their ethnicity (p = .01) and hospital site (p =
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".